Study on the optimization strategy of agricultural industry economic management innovation in the context of rural revitalization in the multi-Internet era
With the implementation of a rural revitalization strategy, the management of the rural industrial economy urgently needs further innovation and optimization. In this paper, principal component analysis is used to identify the key factors of the problems of agricultural and industrial economic manag...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2023.2.00301 |
| _version_ | 1797340768785924096 |
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| author | Guan Lili |
| author_facet | Guan Lili |
| author_sort | Guan Lili |
| collection | DOAJ |
| description | With the implementation of a rural revitalization strategy, the management of the rural industrial economy urgently needs further innovation and optimization. In this paper, principal component analysis is used to identify the key factors of the problems of agricultural and industrial economic management in the context of rural revitalization, and potential indicator factors are uncovered through principal component analysis, and these potential factors are used instead of all indicators for more accurate analysis. Meanwhile, the PCA method was combined with a support vector machine to construct a PCA-SVM model, based on which the influence factors of agricultural economic efficiency were measured. The higher the degree of informationization of agricultural management, the greater the influence factor on agricultural economic benefits, and the correlation rate reached 26.85%. The higher the degree of the system construction of agricultural management, the greater the influence factor on agricultural economic efficiency, and the correlation rate reached 32.14%. The higher the degree of improvement of infrastructure construction, the higher the influence factor on agricultural economic efficiency, with a correlation rate of 35.68%. This study can precisely analyze the current problems in the economic management of the agricultural industry and provide effective references for promoting the economic development of rural areas in the context of rural revitalization. |
| first_indexed | 2024-03-08T10:09:08Z |
| format | Article |
| id | doaj.art-c99f1cfb92f94dc69a2d111d2c1e6ed9 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:09:08Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-c99f1cfb92f94dc69a2d111d2c1e6ed92024-01-29T08:52:31ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.00301Study on the optimization strategy of agricultural industry economic management innovation in the context of rural revitalization in the multi-Internet eraGuan Lili01School of Economics and Management, Zhengzhou Normal University, Zhengzhou, Henan, 450000, China.With the implementation of a rural revitalization strategy, the management of the rural industrial economy urgently needs further innovation and optimization. In this paper, principal component analysis is used to identify the key factors of the problems of agricultural and industrial economic management in the context of rural revitalization, and potential indicator factors are uncovered through principal component analysis, and these potential factors are used instead of all indicators for more accurate analysis. Meanwhile, the PCA method was combined with a support vector machine to construct a PCA-SVM model, based on which the influence factors of agricultural economic efficiency were measured. The higher the degree of informationization of agricultural management, the greater the influence factor on agricultural economic benefits, and the correlation rate reached 26.85%. The higher the degree of the system construction of agricultural management, the greater the influence factor on agricultural economic efficiency, and the correlation rate reached 32.14%. The higher the degree of improvement of infrastructure construction, the higher the influence factor on agricultural economic efficiency, with a correlation rate of 35.68%. This study can precisely analyze the current problems in the economic management of the agricultural industry and provide effective references for promoting the economic development of rural areas in the context of rural revitalization.https://doi.org/10.2478/amns.2023.2.00301principal component analysissupport vector machinerural revitalizationagricultural economic managementpca-svm model01a13 |
| spellingShingle | Guan Lili Study on the optimization strategy of agricultural industry economic management innovation in the context of rural revitalization in the multi-Internet era Applied Mathematics and Nonlinear Sciences principal component analysis support vector machine rural revitalization agricultural economic management pca-svm model 01a13 |
| title | Study on the optimization strategy of agricultural industry economic management innovation in the context of rural revitalization in the multi-Internet era |
| title_full | Study on the optimization strategy of agricultural industry economic management innovation in the context of rural revitalization in the multi-Internet era |
| title_fullStr | Study on the optimization strategy of agricultural industry economic management innovation in the context of rural revitalization in the multi-Internet era |
| title_full_unstemmed | Study on the optimization strategy of agricultural industry economic management innovation in the context of rural revitalization in the multi-Internet era |
| title_short | Study on the optimization strategy of agricultural industry economic management innovation in the context of rural revitalization in the multi-Internet era |
| title_sort | study on the optimization strategy of agricultural industry economic management innovation in the context of rural revitalization in the multi internet era |
| topic | principal component analysis support vector machine rural revitalization agricultural economic management pca-svm model 01a13 |
| url | https://doi.org/10.2478/amns.2023.2.00301 |
| work_keys_str_mv | AT guanlili studyontheoptimizationstrategyofagriculturalindustryeconomicmanagementinnovationinthecontextofruralrevitalizationinthemultiinternetera |